Three-dimensional graphene foam as a biocompatible and conductive scaffold for neural stem cells

Abstract

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This paper, published in 1950, received 539 indexed citations. Written by Ning Li, Qi Zhang, Song Gao, Song Qin, Rong Huang, Long Wang, Liwei Liu, Jianwu Dai, Mingliang Tang and Guosheng Cheng covering the research area of Materials Chemistry, Biomedical Engineering and Cellular and Molecular Neuroscience. It is primarily cited by scholars working on Biomedical Engineering (420 citations), Materials Chemistry (228 citations) and Cellular and Molecular Neuroscience (162 citations). Published in Scientific Reports.

Countries where authors are citing Three-dimensional graphene foam as a biocompatible and conductive scaffold for neural stem cells

Since Specialization
Citations

This map shows the geographic impact of Three-dimensional graphene foam as a biocompatible and conductive scaffold for neural stem cells. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Three-dimensional graphene foam as a biocompatible and conductive scaffold for neural stem cells with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Three-dimensional graphene foam as a biocompatible and conductive scaffold for neural stem cells more than expected).

Fields of papers citing Three-dimensional graphene foam as a biocompatible and conductive scaffold for neural stem cells

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Three-dimensional graphene foam as a biocompatible and conductive scaffold for neural stem cells. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Three-dimensional graphene foam as a biocompatible and conductive scaffold for neural stem cells.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1038/srep01604.

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